In general, an image contrast expansion refers to expanding a gray level range to a maximum gray level range of 0˜255, and its main objective is to increase the dynamic range of the gray level distribution. As to the visual effect, the image contrast is enhanced. For example, an 8-bit 256 gray-level image has a maximum gray level range of 0˜255, but there is a loss of the image gray level distribution range in an actual video transmission due to the signal attenuation of photography, duplication and transmission. In a general 8-bit television video system, the actual number of gray levels of the video display is less than 256, and thus the video contrast will be attenuated, and the video quality will be deteriorated. In addition to the foregoing factors, the properties and parameters of the analog components in the video interface also cause a loss of the image gray level distribution range and adversely affect the displaying effect. For example, since most video decoders decode a received video signal according to its recommended parameters, the gray level range of the decoded image generally falls between 17˜235. Further, the factory default settings of the brightness and contrast of the video interface, the computation of scalar, and the conversion of color matrix will also affect the image gray level distribution range directly.
Traditionally, the image contrast is enhanced to improve the image gray level distribution range, and the dynamic image contrast expansion adjustment technique is applied to process the images, and its method substantially includes the following steps:
1. Firstly, the properties of the image gray level distribution of the three colors: red (R), green (G), and blue (B) of a color image are analyzed. Referring to the image property histogram as shown in FIG. 1, the x-axis represents the gray levels of the image, and the y-axis represents the number of pixels, and the image property histogram is a statistical chart primarily illustrating the number of pixels in each gray level. Therefore, the image property histogram tells the gray level distribution conditions of an image, and thus the image property histogram is usually used for describing the characteristics of an image such as a dark image or a bright image. The area included in the curve of the whole image property histogram represents the total number of pixels of a whole image. Referring to FIG. 2 for the image of a bright screen, the image property histogram of FIG. 3 clearly shows that the main gray level of the image as shown in FIG. 2 is distributed in a high gray level range between 180˜220 and shifted to the right side of the image property histogram. Referring to FIG. 4 for the image of a mid-brightness screen, the image property histogram of FIG. 5 clearly shows that the main gray level of the image as shown in FIG. 4 is distributed in a mid gray level range between 15˜230 and resided in the middle section of the image property histogram. Referring to FIG. 6 for the image of a dark screen, the image property histogram of FIG. 7 clearly shows that the main gray level of the image as shown in FIG. 6 is distributed in a low gray level range between 15˜40 and shifted to the left side of the image property histogram.
2. Secondly, the maximum gray level and minimum gray level required by computing an image contrast expansion are defined. In general, the maximum gray level is obtained by integrating the area from the utmost right side toward the left side of the image property histogram, and its corresponding gray level is defined as the maximum gray level when a critical value of the integrated area is achieved. The minimum gray level is obtained by integrating the area from the utmost left side towards the right side of the image property histogram, and its corresponding minimum gray level is defined if a critical value of the integrated area is achieved. Taking the image processing software, PhotoShop, for example, we define the 5% of the area on the right side of the image property histogram as the maximum gray level (max) and the 5% of the area on the left side of the image property histogram as the minimum gray level (min). Since a color image includes three colors: red, green, and blue, therefore the maximum gray level of the processed image adopts the maximum of the three colors: red, green, and blue and the minimum gray level adopts the minimum of the three color red, green, and blue.
3. The formula for the image contrast expansion is given as follows. After the required maximum gray level (max) and the minimum gray level (min) are obtained, the maximum gray level and the minimum gray level are used to compute a new gray level value Gray′ and an image contrast expansion gain (which has a value k in Formula (2)) of the processed image contrast expansion:
                              Gray          ′                =                  k          ×                      (                          Gray              -              min                        )                                              (        1        )                                k        =                  255                      max            -            min                                              (        2        )            
Since a plasma display panel (PDP) usually comes with a large screen and its structural properties are totally different from those of traditional color cathode ray tubes (CRT), therefore the dynamic contrast expansion technique used for the traditional small-size CRT televisions cannot be used directly for the plasma display panels. It is necessary to make an appropriate modification of the algorithm of the dynamic contrast expansion technique according to the properties of the plasma display panels. The most difficult point is to avoid the flickering of a large plasma display panel, the too-low signal noise ratio (SNR) of a signal at a low gray level, and the noise produced by the contrast expansion, when a dynamic contrast adjustment is made.
The problem of producing noises easily after a contrast expansion is processed for a too-low SNR at a low gray level is described as follows. Referring to FIG. 8 for the measured results after a low gray level white image of a low gray level 4 is produced by a graphic generator, a YPbPr path of a video interface is inputted, and a video decoder is used for decoding, it is obvious that the outputted gray level range of the red and blue colors is 4±3 and the gray level range of the green color is approximately 8±3. Since the gray level distribution ranges of the three colors are plus and minus 3, the SNR of the red and blue colors is defined as 4/3, and the SNR of the green is defined as 8/3. Referring to FIG. 9 for the measured result after a mid gray level white image of a gray level 128 is produced by a graphic generator, a YPbPr path of a video interface is inputted, and a video decoder is used for decoding, it is obvious that the gray level output range of the red color is 121±3, the gray level output range of the green color is approximately 124±2, and the gray level output range of the blue color is 120±3. Now, the SNR of the red color is defined as 121/3, the SNR of the green color is defined as 124/2, and the SNR of the blue color is defined as 120/3. From the description above, the SNR of the image at a low gray level is lower. If it is necessary to amplify the video signal by the digital method, then an obvious noise will be produced at the original position of a low gray level due to the lower SNR. In summation of the description above, it is an important topic for video display manufacturers to apply the dynamic contrast expansion technique to the plasma display panels to improve the image gray level distribution range and video contrast, and effectively avoid the flickering produced in a plasma display panel and the noise due to a low SNR produced after the image at a low gray level is enhanced.